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Get started freeGPT-5.5 vs Claude 4.1 Opus
Compare GPT-5.5 and Claude 4.1 Opus. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | GPT-5.5 | Claude 4.1 Opus |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model Type | text | text |
| Context Window | 1,000,000 tokens | 1,000,000 tokens |
| Input Cost | $5.00/ 1M tokens | $15.00/ 1M tokens |
| Output Cost | $30.00/ 1M tokens | $75.00/ 1M tokens |
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Strengths & Best Use Cases
GPT-5.5
OpenAI1. Strongest Agentic Coding Model
- State-of-the-art on Terminal-Bench 2.0 (82.7%), Expert-SWE (73.1%), and SWE-Bench Pro (58.6%), outperforming GPT-5.4 on complex coding tasks.
- Holds context across large systems, reasons through ambiguous failures, and carries changes through surrounding codebases with fewer tokens.
2. Higher Intelligence at GPT-5.4 Latency
- Co-designed, trained, and served on NVIDIA GB200/GB300 NVL72 systems to match GPT-5.4 per-token latency while performing at a significantly higher level.
- Uses fewer tokens to complete the same tasks, making it more efficient as well as more capable.
3. Powerful for Knowledge Work & Computer Use
- Scores 84.9% on GDPval (44 occupations) and 78.7% on OSWorld-Verified for autonomous computer operation.
- Excels at generating documents, spreadsheets, and reports; naturally moves across finding information, using tools, and checking output.
4. Scientific Research Co-Scientist
- Leading performance on GeneBench, BixBench, and FrontierMath; helped discover a new proof about Ramsey numbers verified in Lean.
- Strong enough to meaningfully accelerate progress at the frontiers of biomedical and mathematical research.
Claude 4.1 Opus
Anthropic1. Advanced Coding Performance
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Achieves 74.5% on SWE-bench Verified, improving the Claude family's state-of-the-art coding abilities.
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Stronger at:
- Multi-file code refactoring
- Large codebase debugging
- Pinpointing exact corrections without unnecessary edits
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Outperforms Opus 4 and shows gains comparable to jumps seen in past major releases.
2. Improved Agentic & Research Capabilities
- Better at maintaining detail accuracy in long research tasks.
- Enhanced agentic search and step-by-step problem solving.
- Performs reliably across complex multi-turn reasoning tasks.
3. Validated by Real-World Users
- GitHub: Better multi-file refactoring and code adjustments.
- Rakuten Group: High precision debugging with minimal collateral changes.
- Windsurf: One standard deviation improvement on their junior dev benchmark - similar magnitude to Sonnet 3.7 → Sonnet 4.
4. Hybrid-Reasoning Benchmark Improvements
- Improvements across TAU-bench, GPQA Diamond, MMMLU, MMMU, AIME (with extended thinking).
- Stronger robustness in long-context reasoning tasks.
Prompts to Get Started
Use these prompts to power AI products you build on Appaca. Each works great with the models above.
Best for GPT-5.5
textProduct Launch Campaign (Messaging + Timeline)
Plan a product launch campaign that highlights your USP and shows how the new offering solves persona challenges.
Account-Based Marketing (ABM) Campaign (Tailored Plays)
Create an ABM campaign targeting high-value accounts with tailored messages that connect persona challenges to your USP.
Lead Scoring System (USP Engagement + Pain Signals)
Design a lead scoring model that prioritizes prospects based on engagement with USP messaging and signals of persona challenge severity.
Best for Claude 4.1 Opus
textExit Ticket Creator
Generate quick formative assessments that gauge student understanding and inform next-day instruction.
Code Review Assistant
Get constructive feedback on your code regarding performance, security, and readability.
Prepare a Case (Outcome Matrix + Preparation Plan)
Map likely outcomes for a dispute and generate a practical preparation plan across facts, evidence, procedure, and settlement.
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